We are seeking a Computer Vision Engineer with strong software and AI fundamentals to build and deploy high-performance AI models.
You will handle the full pipeline—from training detection and segmentation models to optimizing them for production using NVIDIA TensorRT and Docker.
Core Responsibilities Model Training: Train and fine-tune models for Detection, Classification, and Segmentation (e.
g., YOLO, ResNet, U-Net).
Tracking: Implement Multi-Object Tracking (MOT) algorithms for complex video streams.
Engineering: Write production-grade Python code with a focus on modularity and scalability.
Deployment: Containerize applications using Docker for consistent deployment.
3+ years in CV/Deep Learning.
Python, PyTorch, OpenCV.
Strong preference for experience with NVIDIA TensorRT and model optimization (quantization/pruning).
Solid grasp of software engineering principles (Git, testing, CI/CD).
Can work on other non-vision AI implementations